The present invention relates to a data processing system which is programmable in a symbolic processing language, in particular LISP.
LISP is a computer programming language which originated as a tool to facilitate Artificial Intelligence research. Artificial Intellignce is a branch of computer science that seeks to understand and model intelligent behavior with the aid of computers. Intelligent behavior involves thinking about objects in the environment, how objects relates to each other, and the properties and uses of such objects. LISP is designed to facilitate the representation of arbitrary objects and relationships among them. This design is to be contrasted with that of other languages, such as FORTRAN, which are designed to facilitate computations of the values of algebraic formulae, or COBOL, which is designed to facilitate processing the books and records of businesses.
The acronym "LISP" stands for "List Processing Language", as it was dubbed when Professor John McCarthy of MIT (now of Standford University) invented LISP in the 1950's. At that time, the notion of representing data objects and complex relations beween them by "lists" of storage locations was novel. LISP's motion of "object" has been incorporated into many subsequent languages (e.g., SIMULA 67), but management believes that LISP and the languages derived from it are the first choice of Artificial Intelligence researchers all over the world.
LISP also facilitates the modeling of procedural knowledge (i.e., "how to do something" as opposed to "what something is"). All procedural knowledge is expressed as "functions", computational entitites which "know how" to perform some speciifc action or computation upon supplied objects.
Although the text of LISP functions can be from one line to several thousand lines long, the language imposes no penalty for dividing a program into dozens of hundreds of functions, each one the "expert" in some specific task. Thus, LISP facilitates "modularity", the clean division of a program into unique areas of responsibility, with well-defined interaction. The last twenty years of experience in the computer science community has established the importance of modularity for correct program operation, maintenance and intelligibility.
LISP also features "extensible syntax or notation". This means that language constructs are not limited to those supplied, but can include new constructs, defined by the programmer, which are relevant to the problem at hand. Defining new language constructs does not involve modification of the supplied software, or expertise in its internal detals, but is a standard feature of the language available to the applications (and systems) programmer, within the grasp of every beginner. Through this feature, LISP can incorporate new developments in copmuter science.
LISP frees programmers from the responsibility for the detailed management of memory in the computer. The common FORTRAN and PL/I decisions of how big to make a given array or block of memory have no place in LISP. Although it is possible to construct fixed-size arrays, LISP excels in providing facilities to represent arbitrary-size objects, set of unlimited numbers of elements, objects concerning which the number of details or parameters is totally unknown, and so forth. Antiquated complaints of computers above fixed-size data stores ("ERROR, 100 INPUT ITEMS EXCEEDED") are eliminated in systems written in LISP.
LISP provides an "interactive environment", in which all data (knowledge about what things are and how they are) and functions (knowledge about how to do things) co-exist. Data and functions may be inspected or modified by a person developing a program. When an error is discovered in some function or data object, this error may be corrected, and the correction tested, without the need for a new "run". Correction of the error and trial of the repair may sometimes be accomplished in three keystrokes and two seconds of real time. It is LISP's notion of an interactive environment which allows both novices and experts to develop massive systems a layer at a time. It has been observed that LISP experts enter programs directly without need for "coding sheets" or "job decks"; the program is written, entered, and debugged as one operation. Functions can be tested as they are written and problems found. The computer becomes an active participant in program development, not an adversary. Programs developed in this way build themselves from the ground up with solid foundations. Because of these features, LISP program development is very rapid.
LISP offers a unique blend of expressive power and development power. Current applications of LISP span a broad range from computer-aided design systems to medical diagnosis and geophysical analysis for oil exploration. Common to these applications is a requirement for rapidly constructing large temporary data structures and applying procedures to such structures (a data structure is complex configuration of computer memory representing or modeling an object of interest). The power of LISP is vital for such applications.
Researchers at the M.I.T. Artificial Intelligence Laboratory initiated a LISP Machine project in 1974 which was aimed at developing a state-of-the art personal computer design to support programmers developing complex software systems and in which all of the system software would be written in LISP.
The first stage of the project, was a simulator for a LISP machine written on a timeshared computer system. The first generation LISP machine, the CONS, was running in 1976 and a second generation LISP Machine called the CADR incorporated some hardware improvements and was introduced in 1978, replacing the CONS. Software development for LISP machines has been ongoing since 1975. A third generation LISP machine, the LM-2 was introduced in 1980 by Symbolics, Inc.
The main disadvantages of the aforementioned prior art LISP machines and of symbolic language data processing systems in general, is that the computer hardware architecture used in these systems was originally designed for the more traditional software languages such as FORTRAN, COBAL, etc. As a result, while these systems were programmable in symbolic languages such as LISP, the efficiency and speed thereof were considerably reduced due to the inherent aspects of symbolic processing language as explained hereinbefore.